About this Course
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Flexible deadlines

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Intermediate Level

Approx. 7 hours to complete

Suggested: 1 week of study, 5-7 hours/week...


Subtitles: English

Skills you will gain

BigqueryMachine LearningGoogle Cloud PlatformCloud Computing

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 7 hours to complete

Suggested: 1 week of study, 5-7 hours/week...


Subtitles: English

Syllabus - What you will learn from this course

6 minutes to complete


Welcome to the last course in the Data Insights specialization. In this module we will overview the course topics and the labs platform you will be using.

2 videos (Total 6 min)
2 videos
Qwiklabs Overview5m
21 minutes to complete

Introduction to Machine Learning

In this module, we define what Machine Learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels.

6 videos (Total 21 min), 1 quiz
6 videos
Demo: Google Photos2m
What is deep learning?41s
ML Applications for Business3m
ML Terms: Instances, Features, Labels3m
The Spectrum of ML Tools3m
1 practice exercise
Introduction to Machine Learning
2 hours to complete

Pre-trained ML APIs

In this module we will dive into pre-built and pre-trained ML models that we can access (like image recognition and sentiment analysis) within Cloud Datalab.

9 videos (Total 52 min), 2 quizzes
9 videos
Demo: Cloud Translate and Vision APIs5m
Demo: Natural Language Processing API3m
Collaborative Notebooks in the Cloud5m
Demo: Cloud Datalab with BigQuery and Google Analytics7m
Accessing BigQuery datasets from Cloud Datalab15m
Visualizing Datasets in Charts1m
Lab Overview28s
Lab Walkthrough10m
1 practice exercise
Notebooks in the Cloud10m
2 hours to complete

Creating ​ML Datasets in BigQuery

8 videos (Total 35 min), 2 quizzes
8 videos
Choosing good features8m
Exploring and Preprocessing Data1m
Demo: Exploring and Preprocessing Data6m
Other Tools for Creating Data Pipelines50s
Knowing the Unknowable4m
Creating Repeatable Dataset Splits2m
Lab Solution: Creating Repeatable Dataset Splits9m
1 practice exercise
Intro to Machine Learning10m
4 hours to complete

Creating ML Models in BigQuery

In this module, you will learn how to create machine learning models directly inside of BigQuery. You will learn the new syntax and work through the phases of building, evaluating, and testing an ML model.

6 videos (Total 54 min), 1 reading, 3 quizzes
6 videos
Phases of Model Building2m
Demo: Predicting Taxi Cab Fare10m
Demo: Creating a Classification Model12m
Lab Intro: Predicting Visitor Return Purchases with BigQuery2m
Lab Solution: Predicting Visitor Return Purchases in BigQuery20m
1 reading
BigQuery ML Resources10m
1 practice exercise
BigQuery ML
3 minutes to complete

End of Course Recap

You've made it to the end! Let's review the lessons learned in the course and what resources are available for continued learning.

1 video (Total 3 min)
1 video
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Top reviews from Applying Machine Learning to your Data with GCP

By MBJan 22nd 2019

Enjoyed. I would add more in-depth ML part for BigQuery and different scenario. it also good to explain metric how and how to choose right features etc

By LLAug 11th 2018

The instructor Evan is super great to rolling out machine learning in an easy /understandable way. hope he can tech more in-depth of machine learning.

About Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

About the From Data to Insights with Google Cloud Platform Specialization

Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: ● Data Analysts, Business Analysts, Business Intelligence professionals ● Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...
From Data to Insights with Google Cloud Platform

Frequently Asked Questions

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

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